New Mechatronic Systems for the Diagnosis and Treatment of Cancer

Both two dimensional (2D) and three dimensional (3D) imaging modalities are useful tools for viewing the internal anatomy. Three dimensional imaging techniques are required for accurate targeting of needles. This improves the efficiency and control over the intervention as the high temporal resolution of medical images can be used to validate the location of needle and target in real time. Relying on imaging alone, however, means the intervention is still operator dependent because of the difficulty of controlling the location of the needle within the image. The objective of this thesis is to improve the accuracy and repeatability of needle-based interventions over conventional techniques: both manual and automated techniques. This includes increasing the accuracy and repeatability of these procedures in order to minimize the invasiveness of the procedure. In this thesis, I propose that by combining the remote center of motion concept using spherical linkage components into a passive or semi-automated device, the physician will have a useful tracking and guidance system at their disposal in a package, which is less threatening than a robot to both the patient and physician. This design concept offers both the manipulative transparency of a freehand system, and tremor reduction through scaling currently offered in automated systems. In addressing each objective of this thesis, a number of novel mechanical designs incorporating an remote center of motion architecture with varying degrees of freedom have been presented. Each of these designs can be deployed in a variety of imaging modalities and clinical applications, ranging from preclinical to human interventions, with an accuracy of control in the millimeter to sub-millimeter range

Real-time Prostate Motion Tracking For Robot-assisted Laparoscopic Radical Prostatectomy

Radical prostatectomy surgery (RP) is the gold standard for treatment of localized prostate cancer (PCa). Recently, emergence of minimally invasive techniques such as Laparoscopic Radical Prostatectomy (LRP) and Robot-Assisted Laparoscopic Radical Prostatectomy (RARP) has improved the outcomes for prostatectomy. However, it remains difficult for surgeons to make informed decisions regarding resection margins and nerve sparing since the location of the tumour within the organ is not usually visible in a laparoscopic view. While MRI enables visualization of the salient structures and cancer foci, its efficacy in LRP is reduced unless it is fused into a stereoscopic view such that homologous structures overlap. Registration of the MRI image and peri-operative ultrasound image either via visual manual alignment or using a fully automated registration can potentially be exploited to bring the pre-operative information into alignment with the patient coordinate system at the beginning of the procedure. While doing so, prostate motion needs to be compensated in real-time to synchronize the stereoscopic view with the pre-operative MRI during the prostatectomy procedure. In this thesis, two tracking methods are proposed to assess prostate rigid rotation and translation for the prostatectomy. The first method presents a 2D-to-3D point-to-line registration algorithm to measure prostate motion and translation with respect to an initial 3D TRUS image. The second method investigates a point-based stereoscopic tracking technique to compensate for rigid prostate motion so that the same motion can be applied to the pre-operative images

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Computational ultrasound tissue characterisation for brain tumour resection

In brain tumour resection, it is vital to know where critical neurovascular structuresand tumours are located to minimise surgical injuries and cancer recurrence. Theaim of this thesis was to improve intraoperative guidance during brain tumourresection by integrating both ultrasound standard imaging and elastography in thesurgical workflow. Brain tumour resection requires surgeons to identify the tumourboundaries to preserve healthy brain tissue and prevent cancer recurrence. Thisthesis proposes to use ultrasound elastography in combination with conventionalultrasound B-mode imaging to better characterise tumour tissue during surgery.Ultrasound elastography comprises a set of techniques that measure tissue stiffness,which is a known biomarker of brain tumours. The objectives of the researchreported in this thesis are to implement novel learning-based methods for ultrasoundelastography and to integrate them in an image-guided intervention framework.Accurate and real-time intraoperative estimation of tissue elasticity can guide towardsbetter delineation of brain tumours and improve the outcome of neurosurgery. We firstinvestigated current challenges in quasi-static elastography, which evaluates tissuedeformation (strain) by estimating the displacement between successive ultrasoundframes, acquired before and after applying manual compression. Recent approachesin ultrasound elastography have demonstrated that convolutional neural networkscan capture ultrasound high-frequency content and produce accurate strain estimates.We proposed a new unsupervised deep learning method for strain prediction, wherethe training of the network is driven by a regularised cost function, composed of asimilarity metric and a regularisation term that preserves displacement continuityby directly optimising the strain smoothness. We further improved the accuracy of our method by proposing a recurrent network architecture with convolutional long-short-term memory decoder blocks to improve displacement estimation and spatio-temporal continuity between time series ultrasound frames. We then demonstrateinitial results towards extending our ultrasound displacement estimation method toshear wave elastography, which provides a quantitative estimation of tissue stiffness.Furthermore, this thesis describes the development of an open-source image-guidedintervention platform, specifically designed to combine intra-operative ultrasoundimaging with a neuronavigation system and perform real-time ultrasound tissuecharacterisation. The integration was conducted using commercial hardware andvalidated on an anatomical phantom. Finally, preliminary results on the feasibilityand safety of the use of a novel intraoperative ultrasound probe designed for pituitarysurgery are presented. Prior to the clinical assessment of our image-guided platform,the ability of the ultrasound probe to be used alongside standard surgical equipmentwas demonstrated in 5 pituitary cases

Three-dimensional ultrasound scanning

The past two decades have witnessed developments of new imaging techniques that provide three-dimensional images about the interior of the human body in a manner never before available. Ultrasound (US) imaging is an important cost-effective technique used routinely in the management of a number of diseases. However, two-dimensional viewing of three-dimensional anatomy, using conventional two-dimensional US, limits our ability to quantify and visualize the anatomy and guide therapy, because multiple two-dimensional images must be integrated mentally. This practice is inefficient, and may lead to variability and incorrect diagnoses. Investigators and companies have addressed these limitations by developing three-dimensional US techniques. Thus, in this paper, we review the various techniques that are in current use in three-dimensional US imaging systems, with a particular emphasis placed on the geometric accuracy of the generation of three-dimensional images. The principles involved in three-dimensional US imaging are then illustrated with a diagnostic and an interventional application: (i) three-dimensional carotid US imaging for quantification and monitoring of carotid atherosclerosis and (ii) three-dimensional US-guided prostate biopsy